code: def test_feature_union_default(self):
      data = load_iris()
      X, y = data.data, data.target
      X = X.astype(np.float32)
      X_train, X_test, *_ = train_test_split(
          X, y, test_size=0.5, random_state=42
      )
      model = FeatureUnion(
          [("standard", StandardScaler()), ("minmax", MinMaxScaler())]
      ).fit(X_train)
  
      torch_model = hummingbird.ml.convert(model, "torch")
  
      np.testing.assert_allclose(
          model.transform(X_test),
          torch_model.transform(X_test),
          rtol=1e-06,
          atol=1e-06,
      )
  
file_path: hummingbird/tests/test_sklearn_feature_union.py
imports: import unittest
  import numpy
  from sklearn.datasets import load_digits, load_iris
  from sklearn.model_selection import train_test_split
  from sklearn.pipeline import FeatureUnion
  from sklearn.preprocessing import StandardScaler, MinMaxScaler
  import hummingbird.ml
label_desc: Use image node_id 1 for calling the TestSklearnFeatureUnion obj's underlying member method code with example usage: obj.test_feature_union_default() without return types